Overview
This course aims to teach learners how to write GPU-accelerated applications using CUDA 10. By the end of the course, students will understand the fundamentals of CUDA programming and be able to integrate GPU processing into their C and C++ projects. The course covers topics such as the CUDA programming model, NVIDIA Visual Profiler, shared memory, deep learning, concurrency, and streams. The teaching method involves hands-on examples, and learners are expected to have a good understanding of programming in modern C++ (C++17). This course is intended for those interested in leveraging the computational power of GPUs for high-performance computing and developing applications using CUDA.
Syllabus
Learning CUDA 10 Programming : The Course Overview | packtpub.com.
Learning CUDA 10 Programming : The CUDA Programming Model | packtpub.com.
Learning CUDA 10 Programming : The NVIDIA Visual Profiler | packtpub.com.
Learning CUDA 10 Programming : Introduction to Shared Memory | packtpub.com.
Learning CUDA 10 Programming : Deep Learning | packtpub.com.
Learning CUDA 10 Programming : Concurrency and Streams | packtpub.com.
Learning CUDA 10 Programming : What We Have Learned | packtpub.com.
Taught by
Packt Video